In conventional vegetation survey methods, there are mainly two methods. In a first survey method, an identification person surveys a location of plants on foot, and visually determines situations at the location. A second survey method is a method (remote sensing) in which the identification person discriminates the plants by using photographs and images captured by a satellite or an aircraft. These methods are used separately or by combining them.
A sensor using the remote sensing of the second survey method used to be panchromatic (black and white). Recently, a type of the sensor has been changing to be multispectral (colors). Hence, a specialist (identification person) investigates multispectral photographs and images, and the vegetation is identified.
Also, recently, creation of a vegetation map using a Geographic Information System (GIS) has been mainstream. In the GIS, Normalized Difference Vegetation Index (NDVI) is used as reference information, which is prepared beforehand and indicates a crown shape of color for each of plant species, and the plant species are discriminated by conducting pattern matching for the images captured by a camera or the sensor.
Also, in recent years, a satellite (satellite name: EO-1 (sensor name: Hyperion), satellite name: PROBA (sensor name: CHRIS)) mounting a hyperspectral sensor capable of measuring a band, which is ten times more than a conventional multispectral sensor, was launched as a global environmental satellite or the like, and measurement is performed by the hyperspectral sensor. An information amount acquired by using the hyperspectral sensor is dramatically improved. Also, an airborne hyperspectral sensor has been developed, and has begun to be utilized in various fields including environmental and agricultural fields.
Furthermore, as a conventional method of tree species discrimination, a method is known in which image data indicating a forest current state are divided into small segments and the tree species are determined for each of the small segments of the image data. Also, another method is known in which multiple sets of band data are acquired based on an proper time for analysis of the tree species, a mask process is performed for NDVI for each of the tree species by generating a target extraction map for each of the tree species in which an upper and lower limit values are set for a luminance value for each set of the band data, and a tree species distribution is extracted.
A further method is known in which luminance values of the image data of a forest taken from the sky are planarized at peaks and valleys, an area is divided depending on a space change of the luminance values of the image data being planarized, the crown shape and its texture feature amount are calculated, and the tree species is determined based on the texture feature amount of an existing crown.